Hello You!

This is an R Markdown Notebook. When you execute code within the notebook, the results appear beneath the code.

When you save the notebook, an HTML file containing the code and output will be saved alongside it (click the Preview button or press Cmd+Shift+K to preview the HTML file).

The preview shows you a rendered HTML copy of the contents of the editor. Consequently, unlike Knit, Preview does not run any R code chunks. Instead, the output of the chunk when it was last run in the editor is displayed.

You can write HTML (and for instance embed a Google Form)

Load packages

library(gsheet)
library(tidyverse)

Registered S3 methods overwritten by 'dbplyr':
  method         from
  print.tbl_lazy     
  print.tbl_sql      
── Attaching packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.1 ──
✓ ggplot2 3.3.5     ✓ purrr   0.3.4
✓ tibble  3.1.3     ✓ dplyr   1.0.7
✓ tidyr   1.1.3     ✓ stringr 1.4.0
✓ readr   2.0.1     ✓ forcats 0.5.1
── Conflicts ──────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()

library(quanteda)

Package version: 3.1.0
Unicode version: 13.0
ICU version: 69.1
Parallel computing: 16 of 16 threads used.
See https://quanteda.io for tutorials and examples.

library(ggplot2)
library(plotly)

Registered S3 method overwritten by 'data.table':
  method           from
  print.data.table     
Registered S3 method overwritten by 'htmlwidgets':
  method           from         
  print.htmlwidget tools:rstudio

Attaching package: ‘plotly’

The following object is masked from ‘package:ggplot2’:

    last_plot

The following object is masked from ‘package:stats’:

    filter

The following object is masked from ‘package:graphics’:

    layout

Read data and inspect

url <- "https://docs.google.com/spreadsheets/d/1qmbPdvspf9Vg_Eab9fT34ubudF_vklJwKxf0UuJrHvw/edit?usp=sharing"

rawDF <- gsheet2tbl(url)

nameVec <- c("time", "github", "languages", "proficiency")
colnames(rawDF) <- nameVec
summary(rawDF)

     time              github           languages          proficiency  
 Length:2           Length:2           Length:2           Min.   :3.00  
 Class :character   Class :character   Class :character   1st Qu.:3.25  
 Mode  :character   Mode  :character   Mode  :character   Median :3.50  
                                                          Mean   :3.50  
                                                          3rd Qu.:3.75  
                                                          Max.   :4.00  

head(rawDF)

Count languages

languages <- as.character(rawDF$languages) %>% corpus
summary(languages)

Corpus consisting of 2 documents, showing 2 documents:

  Text Types Tokens Sentences
 text1     6      9         1
 text2     3      3         1

dfm <- tokens(languages) %>%
  dfm  %>% convert(to="data.frame") %>%
  select(!contains(",")) %>%
  summarise(across(where(is.numeric), ~ sum(.x, na.rm = TRUE))) %>%
  pivot_longer(everything(), names_to = "language", values_to = "count") 
dfm

Create plots

Simple

proficiency <- table(rawDF$proficiency)
barplot(proficiency,
   xlab="Proficiency Score", ylab="Score Count", col="red")

Styled

p1 <- ggplot(dfm) +
  aes(x=language, y=count, fill=language) +
  geom_col()
p1

Interactive

ggplotly(p1)